Reviewer feedback: One more test w/o monkeypatch

Instead, rely on the installed torch version and skip if it doesn't fit.

skorch/tests/test_net.py

@@ -3064,6 +3064,32 @@ def test_torch_load_kwargs_forwarded_to_torch_load(
         del call_kwargs['map_location']  # we're not interested in that
         assert call_kwargs == expected_kwargs
 
+    def test_torch_load_kwargs_auto_weights_false_pytorch_lt_2_6(
+            self, net_cls, module_cls, monkeypatch, tmp_path
+    ):
+        # Same test as test_torch_load_kwargs_auto_weights_only_false_when_load_params
+        # but without monkeypatching get_torch_load_kwargs. There is no corresponding
+        # test for >= 2.6.0 since it's not clear yet if the switch will be made in that
+        # version.
+        # See discussion in 1063.
+        from skorch._version import Version
+
+        if Version(torch.__version__) >= Version('2.6.0'):
+            pytest.skip("Test only for torch < v2.6.0")
+
+        net = net_cls(module_cls).initialize()
+        net.save_params(f_params=tmp_path / 'params.pkl')
+        state_dict = net.module_.state_dict()
+        expected_kwargs = {"weights_only": False}
+
+        mock_torch_load = Mock(return_value=state_dict)
+        monkeypatch.setattr(torch, "load", mock_torch_load)
+        net.load_params(f_params=tmp_path / 'params.pkl')
+
+        call_kwargs = mock_torch_load.call_args_list[0].kwargs
+        del call_kwargs['map_location']  # we're not interested in that
+        assert call_kwargs == expected_kwargs
+
     def test_custom_module_params_passed_to_optimizer(
             self, net_custom_module_cls, module_cls):
         # custom module parameters should automatically be passed to the optimizer